Scaling <i>k</i> -Means for Multi-Million Frames: A Stratified NANI Approach for Large-Scale MD Simulations

-means clustering and as a component of hybrid workflows and remove a key barrier to routine, scalable, and reproducible exploration of complex conformational ensembles. The improved NANI implementation is accessible through our MDANCE package: https://github.com/mqcomplab/MDANCE.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2026-04-21
DOI
https://doi.org/10.1021/acs.jcim.5c02741
Primary Topic
3D Shape Modeling and Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Scaling k -Means for Multi-Million Frames: A Stratified NANI Approach for Large-Scale MD Simulations

L Y Chen, Ramón Alain Miranda‐Quintana, Jherome Brylle Woody Santos
Journal of Chemical Information and Modeling
3D Shape Modeling and Analysis
article

Scaling k -Means for Multi-Million Frames: A Stratified NANI Approach for Large-Scale MD Simulations

L Y Chen, Ramón Alain Miranda‐Quintana, Jherome Brylle Woody Santos
article en

Abstract

-means clustering and as a component of hybrid workflows and remove a key barrier to routine, scalable, and reproducible exploration of complex conformational ensembles. The improved NANI implementation is accessible through our MDANCE package: https://github.com/mqcomplab/MDANCE.

Journal of Chemical Information and ModelingVol. 66(9)
University of Florida (US)
National Institute of General Medical Sciences
Climate action
Openalex Percentile: Top 19%
3D Shape Modeling and Analysis
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